From monomer to fibril: Abeta-amyloid binding to Aducanumab antibody studied by molecular dynamics simulation

Alzheimer's disease is one of the most common causes of dementia. It is believed that the aggregation of short Aβ -peptides to form oligomeric and protofibrillar amyloid assemblies plays a central role for disease-relevant neurotoxicity. In recent years, passive immunotherapy has been introduced as a potential treatment strategy with anti-amyloid antibodies binding to Aβ -amyloids and inducing their subsequent degradation by the immune system. Although so far mostly unsuccessful in clinical studies, the high-dosed application of the monoclonal antibody Aducanumab has shown therapeutic potential that might be attributed to its much greater affinity to Aβ -aggregates vs monomeric Aβ -peptides. In order to better understand how Aducanumab interacts with aggregated Aβ -forms compared to monomers, we have generated structural model complexes based on the known structure of Aducanumab in complex with an Aβ_{2 − 7} -eptitope. Structural models of Aducanumab bound to full-sequence Aβ_{1 − 40} -monomers, oligomers, protofilaments and mature fibrils were generated and investigated using extensive molecular dynamics simulations to characterize the flexibility and possible additional interactions. Indeed, an aggregate-specific N-terminal binding motif was found in case of Aducanumab binding to oligomers, protofilaments and fibrils that is located next to but not overlapping with the epitope binding site found in the crystal structure with Aβ_{2 − 7} . Analysis of binding energetics indicates that this motif binds weaker than the epitope but likely contributes to Aducanumab's preference for aggregated Aβ -species. The predicted aggregate-specific binding motif could potentially serve as a basis to reengineer Aducanumab for further enhanced preference to bind Aβ -aggregates vs monomers.     

Alveolar mimics with periodic strain and its effect on the cell layer formation

We report on the development of a new model of alveolar air–tissue interface on a chip. The model consists of an array of suspended hexagonal monolayers of gelatin nanofibers supported by microframes and a microfluidic device for the patch integration. The suspended monolayers are deformed to a central displacement of 40–80 µm at the air–liquid interface by application of air pressure in the range of 200–1,000 Pa. With respect to the diameter of the monolayers, that is, 500 µm, this displacement corresponds to a linear strain of 2–10% in agreement with the physiological strain range in the lung alveoli. The culture of A549 cells on the monolayers for an incubation time of 1–3 days showed viability in the model. We exerted a periodic strain of 5% at a frequency of 0.2 Hz for 1 hr to the cells. We found that the cells were strongly coupled to the nanofibers, but the strain reduced the coupling and induced remodeling of the actin cytoskeleton, which led to a better tissue formation. Our model can serve as a versatile tool in lung investigations such as in inhalation toxicology and therapy.     

S-adenosylmethionine and methylthioadenosine boost cellular productivities of antibody forming Chinese hamster ovary cells

The improvement of cell specific productivities for the formation of therapeutic proteins is an important step towards intensified production processes. Among others, the induction of the desired production phenotype via proper media additives is a feasible solution provided that said compounds adequately trigger metabolic and regulatory programs inside the cells. In this study, S-(5′-adenosyl)- l -methionine (SAM) and 5′-deoxy-5′-(methylthio)adenosine (MTA) were found to stimulate cell specific productivities up to approx. 50% while keeping viable cell densities transiently high and partially arresting the cell cycle in an anti-IL-8-producing CHO-DP12 cell line. Noteworthy, MTA turned out to be the chemical degradation product of the methyl group donor SAM and is consumed by the cells.     

Applying a multiobjective metaheuristic inspired by honey bees to phylogenetic inference

The development of increasingly popular multiobjective metaheuristics has allowed bioinformaticians to deal with optimization problems in computational biology where multiple objective functions must be taken into account. One of the most relevant research topics that can benefit from these techniques is phylogenetic inference. Throughout the years, different researchers have proposed their own view about the reconstruction of ancestral evolutionary relationships among species. As a result, biologists often report different phylogenetic trees from a same dataset when considering distinct optimality principles. In this work, we detail a multiobjective swarm intelligence approach based on the novel Artificial Bee Colony algorithm for inferring phylogenies. The aim of this paper is to propose a complementary view of phylogenetics according to the maximum parsimony and maximum likelihood criteria, in order to generate a set of phylogenetic trees that represent a compromise between these principles. Experimental results on a variety of nucleotide data sets and statistical studies highlight the relevance of the proposal with regard to other multiobjective algorithms and state-of-the-art biological methods.     

Role of tyrosine hot‐spot residues at the interface of colicin E9 and immunity protein 9: A comparative free energy simulation study

The endonuclease activity of the bacterial colicin 9 enzyme is controlled by the specific and high‐affinity binding of immunity protein 9 (Im9). Molecular dynamics simulation studies in explicit solvent were used to investigate the free energy change associated with the mutation of two hot‐spot interface residues [tyrosine (Tyr): Tyr54 and Tyr55] of Im9 to Ala. In addition, the effect of several other mutations (Leu33Ala, Leu52Ala, Val34Ala, Val37Ala, Ser48Ala, and Ile53Ala) with smaller influence on binding affinity was also studied. Good qualitative agreement of calculated free energy changes and experimental data on binding affinity of the mutations was observed. The simulation studies can help to elucidate the molecular details on how the mutations influence protein–protein binding affinity. The role of solvent and conformational flexibility of the partner proteins was studied by comparing the results in the presence or absence of solvent and with or without positional restraints. Restriction of the conformational mobility of protein partners resulted in significant changes of the calculated free energies but of similar magnitude for isolated Im9 and for the complex and therefore in only modest changes of binding free energy differences. Although the overall binding free energy change was similar for the two Tyr–Ala mutations, the physical origin appeared to be different with solvation changes contributing significantly to the Tyr55Ala mutation and to a loss of direct protein–protein interactions dominating the free energy change due to the Tyr54Ala mutation. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Vapour-Liquid Phase Equilibria of n-alkanes by Direct Monte Carlo Simulations

Abstract

We report results of direct Monte Carlo simulations of n-pentane and n-decane at the liquidvapour interface for a number of temperatures. The intermolecular interactions are modeled using the last version of the anisotropic united atom model (AUA4). We have used the local long range correction energy and an algorithm allowing to select randomly with equal probability two different displacements. The liquid and vapour densities are in excellent agreement with experimental data and with those previously calculated using the GEMC method.     

A Modified Valley Restrained Monte Carlo Method to Efficiently Search the Low Energy Structures of Peptides

Abstract

A new Monte Carlo sampling scheme, namely the Modified Valley Restrained Monte Carlo procedure, is used to obtain the global energy minimum conformations for polypeptides, such as Met-enkephalin and Melittin. For each peptide, we found close agreement with previous results from both theoretical and experimental studies. The simple idea for controlling the step size according to the Valley Function, provides useful suggestions in searching the global energy minimum structures, and furthermore helps solve the multiple minima problem.     

A combined steepest descent and genetic algorithm (SD/GA) approach for the optimization of solvation parameters

An accurate solvation model is essential for computer modeling of protein folding and other biomolecular self-assembly processes. Compared to explicit solvent models, implicit solvent models, such as the Poisson-Boltzmann (PB) with solvent accessible surface area model (PB/SA), offer a much faster speed—the most compelling reason for the popularity of these implicit solvent models. Since these implicit solvent models typically use empirical parameters, such as atomic radii and the surface tensions, an optimal fit of these parameters is crucial for the final accuracy of properties such as solvation free energy and folding free energy. In this paper, we proposed a combined approach, namely SD/GA, which takes the advantage of both local optimization with the steepest descent (SD), and global optimization with the genetic algorithm (GA), for parameters optimization in multi-dimensional space. The SD/GA method is then applied to the optimization of solvation parameters in the non-polar cavity term of the PB/SA model. The results show that the newly optimized parameters from SD/GA not only increase the accuracy in the solvation free energies for ～200 organic molecules, but also significantly improve the free energy landscape of a β-hairpin folding. The current SD/GA method can be readily applied to other multi-dimensional parameter space optimization as well.     

New potential model for molecular dynamic simulation of liquid HF. I—Parameter optimization for charge equilibration method

In order to build a complete potential model to perform classical molecular dynamic simulations of liquid HF, a new optimization method is proposed to obtain transferable parameters for charge equilibration method on the basis of ab initio reference data. The optimized parameters (the electronegativity χ and the Slater orbital exponent ζ for H and F atoms) appear to be able to reproduce the variations of the electrostatic potential calculated from an ab initio method in a liquid phase of HF molecules for different thermodynamic conditions. It is concluded that the proposed method is general, precise and efficient to obtain transferable and realistic parameters.     

Molecular dynamics simulation of the Al2O3 film structure during atomic layer deposition

Based on an understanding of atomic layer deposition (ALD) from prior experimental and computational results, all-atom molecular dynamics (MD) simulations are used to model the Al₂O₃ film structure and composition during ALD processing. By separating the large time-scale surface reactions from the small time-scale structural relaxation, we have focused on the growth dynamics of amorphous Al₂O₃ films at the atomic scale. The simulations are able to reproduce some important properties and growth mechanisms of Al₂O₃ ALD films, and hence provide a bridge between atomic-level information and experimental measurements. Information about the evolution of the microscopic structures of the Al₂O₃ films is generated, and the influence of operation parameters on the Al₂O₃ ALD process. The simulations predict a strong influence of the initial surface composition and process temperature on the surface roughness, growth rate and growth mode of the deposited films.